US8526525B2 - Interference avoiding MIMO - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
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- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
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- H04B7/086—Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming
Definitions
- MIMO Multiple Input Multiple Output
- a radio wave transmitted from each antenna element is adjusted in amplitude and phase so as to maximize the transmit-array's radiated power in the direction of the receive array.
- the present application relates, in general, to methods of communicating by radio between at least two terminals, each having multiple transmitting elements and multiple receiving elements.
- embodiments can achieve higher speed wireless communication in the presence of an interfering signal by employing multiple antenna elements at both receive and transmit stations, weighted to reduce sensitivity to the interfering signal.
- FIG. 1 shows the basic mathematical model used for phased array antenna calculations.
- FIG. 2 shows a block diagram of a transmitting and receiving system usable with some embodiments.
- FIG. 3 shows a flow chart of calculating the transmitter and receiver weighting factors, given the covariance matrix for an interfering signal.
- FIG. 4 shows a flow chart of the receiver optimization.
- FIG. 5 shows a flow chart of steps to estimate the interference covariance matrix.
- FIG. 6 shows an obstruction between two transceivers.
- FIG. 7 shows using the troposphere to overcome an obstruction between two transceivers.
- FIG. 8 shows using the troposphere to overcome earth curvature between two transceivers.
- FIG. 9 shows an application of an embodiment wherein the desired weights are selected to avoid responding to an interfering signal, and to route the desired signal through a reflective and/or scattering region.
- This disclosure is drawn, inter alia, to methods, apparatus, computer programs and systems related to interference avoiding MIMO.
- Antenna systems are widely used in both ground based applications (e.g., cellular antennas) and airborne applications (e.g., airplane or satellite antennas).
- Such antennas may be in the form of an array having two or more antenna elements that are spatially arranged and electrically interconnected to produce a directional radiation pattern.
- Array beam forming techniques exist and are that can yield multiple, simultaneously available beams directed toward desired spatial locations.
- the beams can be made to have high gain and low sidelobes, or to have a controlled beamwidth.
- the response of the antenna array can also be controlled to produce nulls at desired spatial locations.
- so-called “smart” antenna systems such as adaptive or phased array antennas, combine the outputs of multiple antenna elements with signal processing capabilities to transmit and/or receive communications signals (e.g., microwave signals, RF signals, etc.). As a result, such antenna systems can vary the transmission and/or reception pattern of the communications signals.
- a related application of an antenna array is for beam scanning.
- beam scanning a single main beam of an array is steered and the direction can be varied either continuously or in small discrete steps.
- Techniques for beam scanning are similar to techniques for producing multiple beams and/or nulls.
- Adaptive beam forming techniques dynamically adjust the array pattern to optimize some characteristic of the received signal. For instance, a spatial pattern of beams and nulls that increases the antenna response to a desired signal, while decreasing the antenna response to an unwanted signal.
- Antenna arrays using adaptive beam forming techniques can reject interfering signals having a direction of arrival different from that of a desired signal.
- Multipolarized arrays can also reject interfering signals having different polarization states from the desired signal, even if the signals have the same direction of arrival.
- the interconnection between elements can provide an adjustable phase to each element or can form a phased array.
- the phases (and usually the amplitudes) of the feed network are adjusted to optimize the received signal.
- the geometry of an array and the patterns, orientations, and polarizations of the elements influence the performance of the array.
- Beam forming and beam scanning are generally accomplished by phasing the feed to each element of an array so that signals received or transmitted from all elements will be in phase in a particular direction. This is the direction of the beam maximum. Beam forming and beam scanning techniques are typically used with linear, circular, or planar arrays but some approaches are applicable to any array geometry. Array beams can be formed or scanned using either phase shift or time delay systems.
- a full adaptive array utilizes correlation techniques and feedback control to apply amplitude and phase weights commensurate with the radiation environment to each array element to achieve minimum interference.
- Complex weights for each element of the array can be calculated to optimize some property of the received signal. This does not always result in an array pattern having a beam maximum in the direction of the desired signal but can yield an optimal array output signal. Most often this is accomplished by forming nulls in the directions of interfering signals. Adaptive beam forming is an iterative approximation of optimum beam forming.
- FIG. 1 A general array with variable element weights is shown in block-diagram form in FIG. 1 .
- the output of the array y(t) is the weighted sum of the received signals s i (t) at the array elements having patterns g m (the patterns include gain g) and the thermal noise n(t) from receivers connected to each element.
- the patterns g m are functions of the azimuth angle ⁇ and elevation angle ⁇ of the respective array element m.
- s 1 (t) is the desired signal, and the remaining L signals are considered to be interferers.
- the weights w m are iteratively determined based on the array output y(t), a reference signal d(t) which approximates the desired signal, and previous weights.
- the reference signal is assumed to be identical to the desired signal. In practice this can be achieved or approximated using a training or synchronization sequence, or pilot signals.
- each antenna element typically has a respective phase shifter and/or gain element associated therewith.
- the phase shifters/gain elements may be controlled by a central controller, for example, to adjust respective phases/gains of the antenna elements across the array.
- a central controller for example, to adjust respective phases/gains of the antenna elements across the array.
- phased array antenna Another configuration of a phased array antenna is that the array of elements may be arranged in sub-groups, and each of the sub-groups used for different antenna beams to thus provide multi-beam operation.
- the array of elements may be arranged in sub-groups, and each of the sub-groups used for different antenna beams to thus provide multi-beam operation.
- one potential drawback of such multiple beam arrays is that “friendly” signals arriving on one of the beams can be interfered with (i.e., jammed) even by friendly signals arriving on another beam.
- Phased array antennas allow the electronic steering of an antenna beam in any direction and with high antenna gain by controlling the phase at each antenna element.
- a beam can be “moved in space” using entirely electronic means through control of the phase and amplitude at each antenna element used to generate the beam.
- This beam steering technique is much more compact and much faster than mechanically steered arrays.
- phased arrays allow the creation of deep nulls in the radiation pattern to mitigate strong interference signals from several different directions.
- a conventional phased array system uses a phased array as for at least one of either the transmitter or the receiver.
- Multiple Input, Multiple Output (“MIMO”) as used herein refers to a system having a phased array at both the transmitter and receiver.
- Existing algorithms determine the phased array weights by analyzing the channel between the transmitter and the receiver. Transmitter phased array weights are selected to maximize the radiated power in the direction of the receiver, and the receiver phased array weights are selected to maximize gain in the direction of the transmitter.
- some embodiments include a method for communicating a radio signal between a first station and a second station.
- the method includes estimating at least one characteristic of a radio channel from the first station having a first plurality of weightable transceiving elements, to the second station having a second plurality of weightable transceiving elements; calculating a receive weighting of at least one weightable transceiving element at the second station, responsive to the estimate; calculating a transmit weighting of at least one weightable transceiving element at the first station; weighting the first plurality of weightable transceiving elements with the transmit weighting to form transmit-weighted transceiving elements at the first station; weighting the second plurality of weightable transceiving elements with the receive weighting to form receive-weighted transceiving elements at the second station and then communicating the radio signal by transmitting from the transmit-weighted transceiving elements at the first station, over the radio channel, to the receive-weighted transceiving elements at the second station.
- Estimating at least one characteristic of the radio channel may further include transmitting a predetermined pilot signal from the first station to the second station.
- the estimation of a characteristic of the radio channel may include estimating the amplitude response and/or the phase response between at least one of the transceiving elements of the first station and at least one of the transceiving elements of the second station.
- at least one transmit weighting of the first station may be further responsive to at least one receive weighting of the second station.
- the estimation of a characteristic of the radio channel may be repeated at a later point in time.
- the estimates may also averaged over time or over frequency.
- the estimation of a characteristic of the radio channel may include the sub-steps of estimating the characteristic of the radio channel between all or some of the antenna elements from the first station and all or some of the antenna elements from the second station. From these estimates, a channel estimate matrix is formed.
- the vectors ⁇ t A ,r A ,t B ,r B ⁇ that weigh the transmit signals and the receive signals at the antenna arrays A and B respectively are arrived at in a way that is optimal (“maximum signal-to-noise ratio”), given both channel condition (C A ,C B ) and interference environment (I A ,I B ). Since both channel and interference conditions are a priori unknown and potentially change with time, the algorithm typically executes in a real-time manner in order to adapt to changes.
- MIMO both classical and interference-avoiding MIMO
- direction does not necessarily correspond to a physical direction of arrival, but may refer to a vector of weights in an abstract channel space. MIMO then aligns the transmit weight vector and receive weight vectors in preferred directions within the abstract channel space. Interference-avoiding MIMO additionally nulls out interfering directions within the abstract channel space.
- MIMO in general, and interference-avoiding MIMO in particular, do not necessarily create increased signal-to-noise ratio (SNR) by means of coherence.
- MIMO may create improved SNR by means of diversity in the number of paths, i.e., if there are N-squared paths between the transmit array and the receive array, with “N” being the number of antennas at each end, then the probability that all of the paths together fail to provide a reliable communication path is very small, even if the reliability of any one path is low.
- interference-avoiding MIMO is able to reduce the effect of interference, even if both desired signal and interference lack coherence across the receive array.
- Orientation of the array is not important, because MIMO operates in a rich scattering environment that does not preserve coherence.
- a convenient and portable antenna arrangement may be used for some applications.
- Antenna element separation should be at least 50 ⁇ within each array, so that paths between the antenna elements are sufficiently statistically uncorrelated for reason of diversity.
- Some embodiments may be used with other devices that improve communication reliability and speed, such as error-correcting codes, interleavers, contention resolution schemes such as automatic-repeat request, etc. If these embodiments are used with a communication scheme that divides information flow across channels (slots) in time or frequency or both, the embodiment may be applied to the individual channels constituting the multiplexing scheme. That is, a different set of weights and resulting beam patterns can be applied to different time slots within a time-division multiplexed signal (e.g., TDM 1 . . . TDM N ), and/or to different sub-carriers within a frequency-division multiplexed signal.
- TDM 1 . . . TDM N time-division multiplexed signal
- embodiments may be used in a time-, frequency- or code-division multiplexing (TDMA/FDMA/CDMA) scheme.
- embodiments may be used for each sub-carrier of an orthogonal frequency division multiplex (OFDM) system.
- OFDM orthogonal frequency division multiplex
- TDM 1 may support a point-to-point connection
- TDM 2 may support a point-to-multipoint connection
- TDM 3 may support a multipoint to multipoint connection.
- Some embodiments employ matrix calculations that are known. In particular:
- Some embodiments provide an algorithm that coordinates the actions of multiple transmit-receive links in response to fading and interference conditions.
- the algorithm periodically estimates the channel matrix and the interference covariance and computes and adjusts the transmit weights and the receive weights at each end.
- FIG. 2 shows a transmitter 1 and a receiver 2 , each having a plurality of antenna elements 3 .
- the communications link also may be bidirectional, wherein the transmitter 1 may receive radio frequency (“RF”) energy and the receiver 2 may transmit RF energy.
- RF radio frequency
- the placement of antenna elements 3 is typically in a predetermined, fixed arrangement, and may vary from that shown in FIG. 1 .
- Channel as used herein may refer either to a composite path from the transmitter phased array to the receiver phase array, or may refer to a path from a specific transmitting antenna element 3 to a specific receiving antenna element 3 .
- Phased array weights as used herein may include complex weights, which adjust both amplitude and phase simultaneously. Therefore, weights or phased array weights will be understood to include both amplitude weighting and phase shifting, unless specifically limited otherwise. The intended usage of all terms will be clear from the context of usage.
- the plurality of antenna elements 3 together with adjustable phase shifters 4 and amplitude weights 5 acts as a phased array antenna.
- a similar plurality of antenna elements, adjustable phase shifters and amplitudes weights acts as another phased array antenna.
- the adjustable phase shifters 4 and amplitude weights 5 may be provided in a different order than that shown in FIG. 2 .
- the adjustable phase shifter 4 and amplitude weight 5 may be combined into a complex weighting which simultaneously adjusts phase and amplitude weighting.
- the weighting may be implemented with discrete elements, or may be implemented with a processor digitally applying a complex weighting to the signal received on or transmitted from each of the antenna array elements.
- the transmitter 1 is designated as “station A” and the receiver 2 is designated as “station B”, for the benefit of the mathematical notation presented herein.
- Station A and station B respectively have a and b antenna elements 3 .
- the transmit energy 6 sent from the transmitter 1 to the receiver 2 travels over individual RF channels from transmit antenna j of A to receive antenna i of B, and each of these individual RF channels is designated by c ij .
- the scalar channels c ij are collated into a b ⁇ a matrix, C B , the ij th element of which is c ij .
- Station A constructs an a ⁇ b channel matrix C A .
- Station A experiences interference that is characterized by an interference covariance matrix I A
- Station B experiences interference with covariance I B
- the vector of weights to be applied at to the outgoing stream at A is denoted by t A (an a ⁇ 1 vector)
- the vector to be applied to the incoming stream at A is denoted r A (an a ⁇ 1 vector).
- the equivalent vectors at Station B are denoted t B and r B , both b ⁇ 1 vectors.
- the superscript dagger ( ⁇ ) is used here to indicate the conjugate-transpose of a matrix.
- the phased array antenna of transmitter 1 operates in this embodiment by adjusting in amplitude and phase the RF energy transmitted from each antenna element 3 , so as to maximize the radiated power of the transmit-array in the direction of the receive array.
- the phased array antenna of receiver 2 in this embodiment is adjusted to maximize the gain of the receive-array in the direction of the transmit-array.
- the adjustments to amplitude and phase done at transmit and receive ends are equivalent to multiplication of the baseband signal by complex weights ⁇ t A ,t B ⁇ and ⁇ r A ,r B ⁇ discussed above.
- the algorithm includes two threads in this embodiment, as depicted in FIGS. 3 and 4 .
- One thread (“Thread-I”) carries out the computations needed to arrive at the optimal transmit ( ⁇ t A ,t B ⁇ ) and receive ( ⁇ r A ,r B ⁇ ) weights.
- the other thread (“Thread-II”) determines the receive covariance matrix, which is an auxiliary matrix used by the first thread. First Thread-I is described, then Thread-II.
- Thread-I is shown in the flow chart of FIG. 3 .
- the receive covariance matrix is denoted R A at Station A and R B at Station B.
- Thread-I has access to the latest estimate of the receive covariance matrix as computed by Thread-II.
- Thread-I is divided into five phases, as follows.
- Pilot Transmittal Block 30 of FIG. 3 shows “pilot symbols” which are periodically transmitted by each antenna element of each station. “Pilot symbols” are symbols known to both A and B, thus their information content is zero. The purpose of sending pilot signals is so that every antenna element of the other station can make a measurement of the channel, by comparing the received noisy pilot signal against the transmitted pilot signal as described below.
- Block 31 of FIG. 3 shows that the noisy pilot symbol received by an antenna element of a station directly indicates the channel (i.e., amplitude and phase) between the particular transmit-receive antenna pair for which the pilot was sent.
- the channel estimate may be improved by averaging across time or frequency or both, as long as the change in the channel estimate over time and/or frequency is small compared to the window used for averaging.
- each station has an estimate of the channel matrix C, wherein each element c ij of channel matrix C represents the channel response from transmitter i to receiver j.
- Block 32 of FIG. 3 shows that each end of the link now executes an iterative algorithm in order to determine the weight-vectors r A and r B .
- the algorithm is shown in FIG. 4 .
- the receiver optimization algorithm executes at Station B as well, with the subscript A replaced by B in the pseudo-code of FIG. 4 .
- the iterative algorithm continues until either a maximum number of iterations has been reached, or the fractional difference between successive r A becomes less than a predetermined threshold.
- Station ‘A’ sends to Station ‘B’ the actual value of the vector r A , and likewise Station ‘B’ sends to Station ‘A’ the actual value of the vector r B .
- Block 34 of FIG. 3 shows that each station determines the optimal transmit weight-vectors t A and t B using the receive vector of the other party. If that were not the case, i.e., if the transmit vector was derived by a party's own receive vector, there would be no need to exchange the receive vectors r A and r B between the two sides. Interference avoiding MIMO optimizes transmit weights so as to direct energy not necessarily directly towards the receiver, but possibly towards some other scatterer. The receiver co-operatively looks towards the scatterer, thereby reducing the antenna response in the direction of an interference. If the desired signal and the interference both come from the exact same direction, then it would be impossible to eliminate the interferer without getting the transmitter to modify its talk-direction.
- the equations involved in transmitter optimization are:
- Block 35 of FIG. 3 shows that traffic symbols may now be sent using the just-obtained transmit weights ⁇ t A ,t B ⁇ , and may be received using the just-obtained receive weights ⁇ r A ,r B ⁇ . Since both channel and interference conditions are liable to change with time, pilot symbols are periodically re-sent, thereby triggering the remaining steps of Thread-I. In this way the transmit- and receive weights ⁇ t A ,r A ,t B ,r B ⁇ are periodically re-computed in order to adapt to a changing environment.
- FIG. 4 shows further details of the receiver optimization shown in block 32 of FIG. 3 .
- FIG. 5 shows the pseudo-code for Thread-II, according to one embodiment.
- Thread-II periodically updates an estimate of the receive covariance matrix, and to supply this matrix to Thread-I upon demand.
- the receive covariance matrix is simply a time average of the outer product of the vector of signals received at an array.
- the averaging can be done in any number of ways, for example using a fixed-length window (i.e., FIR-filter averaging), or in an auto-regressive manner (i.e., IIR-filter averaging) or some combination of both.
- the receive covariance matrix is estimated in an auto-regressive manner.
- ⁇ represents a forgetting factor
- the vector x A represents the vector of signals received by the antenna array at Station A.
- the forgetting factor ⁇ may be set to a number close to unity (say 0.999) if the interference environment is expected to be stationary, or it may be set away from unity (say 0.9) if the interference environment is expected to change rapidly.
- a similar procedure would hold at Station B, with subscript A replaced by B.
- Thread-I and Thread-II continually updates the transmit weights and the receive weights so that a direction of transmission and reception is selected in order to improve the desired signal, while avoiding the effects from an unwanted interference.
- a direct transmission path from transmitter to receiver may not be available.
- there may be an obstruction between the transceiver 100 and transceiver 200 wherein a transceiver combines the functions of both a transmitter 1 and a receiver 2 .
- the transmitter and receiver may be over the horizon from each other.
- there may be an obstruction between the transmitter and receiver for instance a mountain. In this situation, a reflection path may be available, as shown in FIGS. 7 and 8 .
- the reflection path may include a scattering means capable of changing the direction of propagation of RF energy, for instance reflective particles; ionized particles; tropospheric scattering; changes in the refractive index of the communication path, for instance refractive index changes caused by changes in one or more characteristic of layers of the atmosphere, such as temperature or density; ground reflections; reflections from man-made objects such as buildings or objects that are airborne, tethered, or suspended; natural objects such as a cliff or mountain; or any combination of these means.
- the scattering means is in a position that is used to redirect the desired RF energy, while avoiding unwanted RF energy (i.e., the interference).
- RF interference In another example, unwanted RF interference is present.
- RF interference of some form is inherent in the vast majority of wireless communication, and it is desirable to minimize the effect of the unwanted RF interference upon transmission link performance.
- Examples of communication systems susceptible to RF interference include cellular communication, terrestrial wireless microwave links, short-range LAN wireless, air-traffic communication and sea-traffic communication.
- Such communication systems may have industry-wide technology standards governing the wireless transmission design and performance.
- examples of technology standards include Global System for Mobile communications (GSM), CDMA2000, Wideband Code Division Multiple Access (WCDMA), Evolution-Data Optimized (EV-DO), High Speed Packet Access (HSPA) and their variants, all of which are well know to persons skilled in the art of cellular communication.
- GSM Global System for Mobile communications
- CDMA2000 Wideband Code Division Multiple Access
- WCDMA Wideband Code Division Multiple Access
- EV-DO Evolution-Data Optimized
- HSPA High Speed Packet Access
- WiFi IEEE-802.11
- WiMax IEEE-802.16 family of standards
- usage of multiple antennas at either one end or both ends of the transmission link may improve the transmission link quality, and/or improve the bit rate available over the transmission link for a given link quality.
- the MIMO technique described herein can be used to employ multiple antennas.
- An interference avoiding MIMO communication system may adaptively reconfigure the antenna response, for instance by using a reflection region 81 having an advantageous response or channel characteristic, between the transmitter 1 and receiver 2 , compared to a direct path between the transmitter 1 and receiver 2 .
- the transmitter and receiver antenna weights are continually updated to track changes in the transmission characteristics of the channel, primarily to compensate for apparent changes in position of the interfering signal 80 .
- the transmit antenna weights and receive antenna weights may also be changed to improve the response to the desired signal between the transmitter and receiver, in response to changes arising from time-varying changes to the channel characteristics.
- the interference avoiding MIMO communication system described herein may be used at least with the cellular communication, terrestrial wireless microwave links, short-range LAN wireless, air-traffic communication and sea-traffic communication systems discussed above.
- the implementer may opt for a mainly hardware and/or firmware vehicle; if flexibility is paramount, the implementer may opt for a mainly software implementation; or, yet again alternatively, the implementer may opt for some combination of hardware, software, and/or firmware.
- a signal bearing medium examples include, but are not limited to, the following: a recordable type medium such as a floppy disk, a hard disk drive, a Compact Disc (CD), a Digital Video Disk (DVD), a digital tape, a computer memory, etc.; and a transmission type medium such as a digital and/or an analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link, etc.).
- a typical data processing system generally includes one or more of a system unit housing, a video display device, a memory such as volatile and non-volatile memory, processors such as microprocessors and digital signal processors, computational entities such as operating systems, drivers, graphical user interfaces, and applications programs, one or more interaction devices, such as a touch pad or screen, and/or control systems including feedback loops and control motors (e.g., feedback for sensing position and/or velocity; control motors for moving and/or adjusting components and/or quantities).
- a typical data processing system may be implemented utilizing any suitable commercially available components, such as those typically found in data computing/communication and/or network computing/communication systems.
- any two components so associated can also be viewed as being “operably connected”, or “operably coupled”, to each other to achieve the desired functionality, and any two components capable of being so associated can also be viewed as being “operably couplable”, to each other to achieve the desired functionality.
- operably couplable include but are not limited to physically mateable and/or physically interacting components and/or wirelessly interactable and/or wirelessly interacting components and/or logically interacting and/or logically interactable components.
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